code: def test_get_flavor_configuration_throws_exception_when_model_configuration_does_not_exist(
      model_path,
  ):
      with pytest.raises(
          MlflowException,
          match='Could not find an "MLmodel" configuration file',
      ) as exc:
          mlflow_model_utils._get_flavor_configuration(
              model_path=model_path,
              flavor_name=mlflow.mleap.FLAVOR_NAME,
          )
      assert exc.value.error_code == ErrorCode.Name(
          RESOURCE_DOES_NOT_EXIST
      )
  
file_path: mlflow/tests/utils/test_model_utils.py
imports: import os
  import sys
  import pytest
  import sklearn.neighbors
  from sklearn import datasets
  import mlflow.sklearn
  import mlflow.utils.model_utils
  from mlflow.exceptions import MlflowException
  from mlflow.mleap import FLAVOR_NAME
  from mlflow.models import Model
  from mlflow.protos.databricks_pb2 import RESOURCE_DOES_NOT_EXIST, ErrorCode
  from mlflow.utils.file_utils import TempDir
label_desc: Use image node_id 3 for calling a global function with example usage: test_get_flavor_configuration_throws_exception_when_model_configuration_does_not_exist(model_path) without return types